This guide uses the latest Azure Cosmos DB JavaScript module (released as final version just 17 days ago). Additionally, this article is based on the ES 2017 standard. The async / await syntax makes the code short and readable. In contrast to many other tutorials, this article focuses on the minimum code required to understand the concepts.

From the perspective of a C# developer, the introduction of Async and Await into the latest JavaScript version (ECMAScript 2017+) is a welcome addition. It makes asynchronous code a lot cleaner and more readable.

However, a lot of legacy libraries and code snippets are out there. It’s usually difficult to go all-in with async/await. This article is a short intro to error handling and the evolution of asynchronous development in JavaScript.

Error Handling in JavaScript

Most asynchronous operations like web requests can cause an error. Thus, let’s spend a minute reviewing the basics of the code flow.

In this last part, we bring the vital sign check list to life. Artificial Intelligence interprets assessments spoken in natural language. It extracts the relevant information and manages an up-to-date, browser-based checklist. Real-time communication is handled through Web Sockets with Socket.IO.

The example scenario focuses on a vital signs checklist in a hospital. The same concept applies to countless other use cases.

In this article series, we’re creating a sample app that interprets assessments from vital signs checks in hospitals. It filters out relevant information like the measured temperature or pupillary response. Yet, it’s easy to extend the scenario to any other area.

The vision: automatic checklists, filled out by simply listening to users explaining what they observe. The architecture of the sample app is based on a lightweight architecture: HTML5, Node.js + the LUIS service in the cloud.

Such an app would be incredibly useful in a hospital, where nurses need to perform and log countless vital sign checks with patients every day.

In part 1 of the article, I’ve explained the overall architecture of the service. In this part, we get hands-on and start implementing the Node.js-based backend. It will ultimately handle all the central messaging. It communicates both with the client user interface running in a browser, as well as the Microsoft LUIS language understanding service in the Azure Cloud.

Creating the Node Backend

Node.js is a great fit for such a service. It’s easy to setup and uses JavaScript for development. Also, the code runs locally for development, allowing rapid testing. But, it’s easy to deploy it to a dedicated server or the cloud later.

During the last few years, cognitive services became immensely powerful. Especially interesting is natural language understanding. Using the latest tools, training the computer to understand real spoken sentences and to extract information is reduced to a matter of minutes. We as humans no longer need to learn how to speak with a computer; it simply understands us.

I’ll show how to use the Language Understanding Cognitive Service (LUIS) from Microsoft. The aim is to build an automated check-list for nurses working at hospitals. Every morning, they record the vital sign of every patient. At the same time, they document the measurements on paper checklists.

With the new app developed in this article, the process is much easier. While checking the vital signs, nurses usually talk to the patients about their assessments. The “Vital Signs Checklist” app filters out the relevant data (e.g., the temperature or the pupillary response) and marks it in a checklist. Nurses no longer have to pick up a pen to manually record the information.

It’s important to know the basics of how the web works. In one of the introductionary lectures at Digital Healthcare, we take a look at HTML5, CSS, JavaScript & more. Understanding basic web technology is required to ensure that web sites have excellent usability as well as accessibility.